Community-acquired Klebsiella pneumoniae pneumonia in ICU: a multicenter retrospective study.

BACKGROUND: Alongside the recent worldwide expansion of hypervirulent Klebsiella pneumoniae (KP) infections, the available literature regarding cases of community acquired pneumonias (KP-CAP) remains scarce but reports a strikingly high and early mortality. We performed a retrospective multicenter study (7 ICU in France) between 2015 and 2019, comparing prognosis and severity of KP-CAP versus Streptococcus pneumoniae - CAP (SP-CAP). METHODS: For each KP-CAP, three SP-CAP admitted in ICUs within the same center and within the same 6-month window were selected. When available, KP strains were studied, and bacterial virulence was genetically assessed for virulence factors. The primary outcome was in-hospital mortality. Associations between clinical outcomes and type of infection were tested using univariate and multivariate logistic regressions, adjusted for pairing variables. RESULTS: Twenty-seven KP-CAP and 81 SP-CAP were included. Respective in-hospital mortality rates were 59% (n = 16) and 17% (n = 14, p < 0.001), despite adequate antibiotic therapy. KP-CAP median time from admission to death was 26.9 h [IQR 5.75-44 h] and were significantly associated with higher rates of multiple organ failures (93% vs. 42%, p < 0.001), disseminated intravascular coagulation (12% vs. 1.3%, p = 0.046), septic shock (median lactate on ICU admission 4.60 vs. 2.90 mmol/L, p = 0.030) and kidney failure (KDIGO-3: 87% vs. 44%, p < 0.001). Interestingly, alcoholism was the only identified predisposing factor of KP-CAP. Severity on ICU admission (2-fold higher for KP-CAP) was the only factor associated with mortality in a multivariate analysis. CONCLUSION: We described a strong association between KP-CAP infection and higher and earlier mortality when compared to SP-CAP. Moreover, alcoholism was the sole predisposing factor associated with KP-CAP infection. These findings should raise awareness of clinicians involved in the management of severe CAP about this microbiological etiology. Future prospective studies are needed to confirm these results and to design strategies to improve the prognosis of such infections.

Modeling the impact of national and regional lockdowns on the 2020 spring wave of COVID-19 in France.

Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like "where" and "when" still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increase. However, the public health costs associated with these delays tend to grow with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality, and stress on the healthcare system.

Evaluating COVID-19 Booster Vaccination Strategies in a Partially Vaccinated Population: A Modeling Study.

BACKGROUND: Several countries are implementing COVID-19 booster vaccination campaigns. The objective of this study was to model the impact of different primary and booster vaccination strategies. METHODS: We used a compartmental model fitted to hospital admission data in France to analyze the impact of primary and booster vaccination strategies on morbidity and mortality, assuming waning of immunity and various levels of virus transmissibility during winter. RESULTS: Strategies prioritizing primary vaccinations were systematically more effective than strategies prioritizing boosters. Regarding booster strategies targeting different age groups, their effectiveness varied with immunity and virus transmissibility levels. If the waning of immunity affects all adults, people aged 30 to 49 years should be boosted in priority, even for low transmissibility levels. CONCLUSIONS: Increasing the primary vaccination coverage should remain a priority. If a plateau has been reached, boosting the immunity of younger adults could be the most effective strategy, especially if SARS-CoV-2 transmissibility is high.

A modelling study investigating short and medium-term challenges for COVID-19 vaccination: From prioritisation to the relaxation of measures.

BACKGROUND: The roll-out of COVID-19 vaccines is a multi-faceted challenge whose performance depends on pace of vaccination, vaccine characteristics and heterogeneities in individual risks. METHODS: We developed a mathematical model accounting for the risk of severe disease by age and comorbidity, and transmission dynamics. We compared vaccine prioritisation strategies in the early roll-out stage and quantified the extent to which measures could be relaxed as a function of the vaccine coverage achieved in France. FINDINGS: Prioritizing at-risk individuals reduces morbi-mortality the most if vaccines only reduce severity, but is of less importance if vaccines also substantially reduce infectivity or susceptibility. Age is the most important factor to consider for prioritization; additionally accounting for comorbidities increases the performance of the campaign in a context of scarce resources. Vaccinating 90% of ≥65 y.o. and 70% of 18-64 y.o. before autumn 2021 with a vaccine that reduces severity by 90% and susceptibility by 80%, we find that control measures reducing transmission rates by 15-27% should be maintained to remain below 1000 daily hospital admissions in France with a highly transmissible variant (basic reproduction number R0  = 4). Assuming 90% of ≥65 y.o. are vaccinated, full relaxation of control measures might be achieved with a vaccine coverage of 89-100% in 18-64 y.o or 60-69% of 0-64 y.o. INTERPRETATION: Age and comorbidity-based vaccine prioritization strategies could reduce the burden of the disease. Very high vaccination coverage may be required to completely relax control measures. Vaccination of children, if possible, could lower coverage targets necessary to achieve this objective.

Identification of the Best Semantic Expansion to Query PubMed Through Automatic Performance Assessment of Four Search Strategies on All Medical Subject Heading Descriptors: Comparative Study.

BACKGROUND: With the continuous expansion of available biomedical data, efficient and effective information retrieval has become of utmost importance. Semantic expansion of queries using synonyms may improve information retrieval. OBJECTIVE: The aim of this study was to automatically construct and evaluate expanded PubMed queries of the form "preferred term"[MH] OR "preferred term"[TIAB] OR "synonym 1"[TIAB] OR "synonym 2"[TIAB] OR …, for each of the 28,313 Medical Subject Heading (MeSH) descriptors, by using different semantic expansion strategies. We sought to propose an innovative method that could automatically evaluate these strategies, based on the three main metrics used in information science (precision, recall, and F-measure). METHODS: Three semantic expansion strategies were assessed. They differed by the synonyms used to build the queries as follows: MeSH synonyms, Unified Medical Language System (UMLS) mappings, and custom mappings (Catalogue et Index des Sites Médicaux de langue Française [CISMeF]). The precision, recall, and F-measure metrics were automatically computed for the three strategies and for the standard automatic term mapping (ATM) of PubMed. The method to automatically compute the metrics involved computing the number of all relevant citations (A), using National Library of Medicine indexing as the gold standard ("preferred term"[MH]), the number of citations retrieved by the added terms ("synonym 1"[TIAB] OR "synonym 2"[TIAB] OR …) (B), and the number of relevant citations retrieved by the added terms (combining the previous two queries with an "AND" operator) (C). It was possible to programmatically compute the metrics for each strategy using each of the 28,313 MeSH descriptors as a "preferred term," corresponding to 239,724 different queries built and sent to the PubMed application program interface. The four search strategies were ranked and compared for each metric. RESULTS: ATM had the worst performance for all three metrics among the four strategies. The MeSH strategy had the best mean precision (51%, SD 23%). The UMLS strategy had the best recall and F-measure (41%, SD 31% and 36%, SD 24%, respectively). CISMeF had the second best recall and F-measure (40%, SD 31% and 35%, SD 24%, respectively). However, considering a cutoff of 5%, CISMeF had better precision than UMLS for 1180 descriptors, better recall for 793 descriptors, and better F-measure for 678 descriptors. CONCLUSIONS: This study highlights the importance of using semantic expansion strategies to improve information retrieval. However, the performances of a given strategy, relatively to another, varied greatly depending on the MeSH descriptor. These results confirm there is no ideal search strategy for all descriptors. Different semantic expansions should be used depending on the descriptor and the user's objectives. Thus, we developed an interface that allows users to input a descriptor and then proposes the best semantic expansion to maximize the three main metrics (precision, recall, and F-measure).